Should I prefer cropped images or realistic images for object detection?
Google recommandation seems to answer this:

The training data should be as close as possible to the data on which
predictions are to be made.
For example, if your use case involves blurry and low-resolution
images (such as from a security camera), your training data should be
composed of blurry, low-resolution images. In general, you should also
consider providing multiple angles, resolutions, and backgrounds for
your training images.

https://cloud.google.com/vision/automl/object-detection/docs/prepare
Would you agree, also in the case of symbols?